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MultiNest

Purpose

MultiNest in Jarvis-HEP is a static nested-sampling wrapper (using dynesty NestedSampler).

Full Sampling Section Keys

  • Sampling.Method (required): must be MultiNest.
  • Sampling.Variables (required, array):
  • name, description, distribution.type, distribution.parameters
  • Runtime-safe parameter sets: Flat(min,max), Log(min,max), Normal(mean,stddev), Log-Normal(mean,stddev), Logit(location,scale)
  • Sampling.LogLikelihood (required, array): {name, expression}
  • Sampling.selection (optional, string)
  • Sampling.Bounds (required for production use):
  • nlive (required, integer)
  • rseed (required, integer)
  • run_nested (required, object): forwarded to NestedSampler.run_nested(**run_nested)

Full Skeleton

Sampling:
  Method: "MultiNest"
  Variables:
    - name: p1
      description: parameter 1
      distribution:
        type: Flat
        parameters:
          min: 0.0
          max: 1.0
  LogLikelihood:
    - name: L_total
      expression: "-0.5*((obs-100.0)/10.0)^2"
  selection: "p1 > 0"
  Bounds:
    nlive: 600
    rseed: 2026
    run_nested:
      dlogz: 0.05
      maxiter: 80000
      print_progress: true

Example

Sampling:
  Method: "MultiNest"
  Variables:
    - name: xx
      description: x
      distribution:
        type: Flat
        parameters:
          min: 0.0
          max: 31.4159
    - name: yy
      description: y
      distribution:
        type: Flat
        parameters:
          min: 0.0
          max: 31.4159
  LogLikelihood:
    - name: L_z
      expression: "-0.5*((z-100.0)/10.0)^2"
  Bounds:
    nlive: 600
    rseed: 2026
    run_nested:
      dlogz: 0.05
      maxiter: 80000
      print_progress: true